Intelligent selection of transmitter power control (and related rate control) is important in wireless networking for maintaining communication quality in the presence of interference, increasing network capacity, reducing power consumption, and so on. Selecting a high transmit power increases the signal power at the receiver, resulting in a higher signal-to-noise ratio and higher data transmission rates. However, increasing transmit power also results in higher power consumption and higher levels of interference between links. Consequently, techniques for power control involve complicated trade-offs that depend on the specific nature and conditions of the wireless network. Moreover, because these specifics often change in time as devices join and leave the network and as demands on the network change, effective power control must dynamically adapt to these changing conditions. In contrast with centralized power control techniques, distributed power control techniques are further complicated due to the presence of many devices sharing the wireless network and the need to ensure that a given power control technique converges to a stable and desirable power levels for all devices.
The Foschini-Miljanic (FM) algorithm is the seminal distributed transmitter power control technique for wireless networks. It provides distributed power control of ad-hoc networks with user-specific signal-to-interference ratio (SIR) requirements and yields minimum transmitter powers that satisfy those SIR requirements. According to the FM algorithm, each communication link i in the shared wireless channel sets a target signal to interference plus noise ratio (SINR), γi*. Each transmitter then aims to achieve γi* in each time slot by autonomously updating its transmitter power Pit, using the control algorithmPit+1=(γi*/γit)Pit  (1)in consecutive time slots, where γit is the SINR of link i observed in time slot t. The SINR γit of link i observed in time slot t is measured at the receiver of link i and communicated to the transmitter (e.g., over a separate control channel). Thus, although there is intra-link communication from the receiver to the transmitter, there is no cross-link communication and each link acts autonomously, a highly desirable property for scalability. In this sense the FM algorithm is distributed. However, there is need to ensure that the SINR targets γi* are all feasible so that the power levels do not explode. If the target SINRs γi* are feasible for all links i, then the FM algorithm will provably converge to the set SINR targets γi*. If not, all transmit power levels will diverge to infinity. (The asynchronous version of this FM control algorithm converges or diverges similarly.) Therefore, this is an essential global requirement, compromising somewhat the distributed nature of the algorithm. Note that by fixing a target SINR γi*, each link i essentially sets a fixed desirable effective transmission rate, hence, link communication delay. Therefore, the FM algorithm does not manage the delay/power tradeoff, a fundamental issue in wireless communication.
Various other techniques for addressing the power control problem have been proposed. Some aim to maximize the minimum SINR of any link sharing the wireless channel, instead of managing the power/delay tradeoff. Game theoretic and utility maximization approaches require various degrees of link coordination and do not control the delay vs. power tradeoff explicitly. Accordingly, there remains a need for dynamic power control techniques in wireless networks that overcome these limitations.